Here's a fun fact -- most of your data are just noise. But that's not your fault. In a world that requires a pretty high filter to extract the signal from the noise around us, the same holds true for our data. And if you haven’t had a chance to read my first blog post about not all data are created equal or watch the snack break, I’d encourage you to take a look.
There was a popular film from the 70s about Sherlock Holmes called The Seven-Per-Cent Solution. I have my own data sleuthing theory that I think of as the nine percent solution. It goes like this: most customers I encounter only need about nine percent of their data. In that nine percent are things like behavior and propensity to buy. The vast amount of the data organizations collect, however, just sits there collecting dust.
For a long time, marketers have been told that they need a 360-degree view of the customer. So they collect data from sales, services, accounting, operations, third-party data providers, and so on. They’ve ended up with a lot of data—so much so, that marketers began to focus more on how they would store their data (e.g., data mart, data warehouse, data lake) than how they would use it. But if you’ve re-created your data lake in your customer data platform (CDP), you’ve made a terrible mistake.
A CDP isn’t intended to house all your data. Instead, it should be designed to filter out noise in favor of signals. Signals are those data that actually drive marketing outcomes, like increasing customer lifetime value or improving customer engagement. Behavioral data is a signal. Content affinity is a signal. And these signals, taken together, are what create meaningful experiences for your customers.
A customer data platform is a lot different than a data warehouse. A data warehouse is capable of holding a truly staggering amount of data. Billions of records. Thousands of fields. Years of history. But the sheer volume of the data in the warehouse makes it impossible to use that data in all the places you need to. And let's forget about any notion of real-time availability. Personalization-at-scale and the future of marketing require marketers to be much more nimble than a data warehouse can possibly accommodate, which is often at least part of the motivation for acquiring a CDP in the first place.
If you're not careful, you could still end up with an abundance of noise in your CDP if you intend to use it as a data warehouse. Instead, you should think of a CDP as an intelligence and activation center. Across all the marketers I've worked with, after bringing in hundreds of fields on their users, they only end up using about 9% of them. This means that most of the time you spent wrangling data, you could have been wrangling customers.
You can’t buy proprietary data like propensity to buy, content affinities, or predictive behaviors. And you can’t afford to spend months sifting through mountains of data to find it. The best metric for a marketing technology investment is time to value: How long does it take before an investment begins to deliver value to our business and to our customers? Lytics identifies the signals in your business data that reveal affinities and predictive behaviors and puts them to work in your marketing campaigns and content recommendations almost immediately. Compare that to earlier data analytics initiatives, where you’d still be stuck in the extraction, transformation, and loading (ETL) phase of the project after three weeks, make that 3 months or even 3 years! (Yes, I have had that experience.)
While three weeks sounds fast, and it is, your business needs to be providing all visitors and customers with personalized experiences out of the gate. The world has changed, COVID-19 made the transition to online business almost complete. Organizations don’t have time to enter digital transformation slowly. Personalized content is what differentiates brands, creates meaningful experiences, and drives higher engagement. With Lytics, you can begin delivering these personalized experiences out of the box, without unpacking a warehouse full of data.
Using the wrong data can box your customers into broad segments that never feel personal. Having the right data out of the box is like having Sherlock Holmes on your side to tell you everything important that you need to know about your customers. And the importance of knowing your customers is an elementary truth that every marketer can agree on.
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